Artificial Intelligence @ Helbling

Visionary possibilities

The advanced application of AI in our clients’ industries, including robotics, MedTech, processes, and manufacturing, is transforming these sectors in a profound way.

The dream of autonomous robots or systems capable of making independent decisions with little or no human interaction has inspired not only scientists and engineers, but also common trivia and pop culture – like HAL 9000, Stanley Kubrick’s fictional AI character. Today’s advancements in chip technology, machine learning and the development of advanced computing (such as neuromorphic sensors) certainly have brought us a lot closer to assessing AI’s potential impacts. This includes advancements in AI algorithms like deep reinforcement learning, neuromorphic computing and simultaneous localization and mapping (SLAM) to enhance navigation and decision-making capabilities.

The development of foundational world models like Google’s Genie 2 and Nvidia’s Cosmos plays a crucial role in the development of artificial general intelligence (AGI). They generate diverse, dynamic 3D environments, allowing AI agents to train in virtually unlimited scenarios, which is essential for developing robust and generalized AI systems. Their impact extends beyond simulation to robotics and other areas, providing AI with a deeper understanding of the physical world, which is crucial for achieving AGI.

What is behind the hype and what does reality look like for our clients?

The dream of autonomous robots capable of making independent decisions has become increasingly tangible with advancements in machine learning and computer vision. However, for midsize manufacturing companies like many of our clients, full autonomy remains a distant goal because of high costs, complex implementation, lack of high-quality data and the need for skilled experts. Practical use cases like predictive maintenance and automated quality control offer more achievable and cost-effective opportunities in the short term. Investing in these technologies should be guided by clear return of investment expectations and a focus on incremental improvements rather than chasing futuristic AGI capabilities. By starting with the easiest opportunities and leveraging proven tools, midsize manufacturers can improve efficiency and remain competitive without overextending their resources.

The integration of large language models (LLMs) like ChatGPT or Llama into the processes of midsize manufacturing companies presents several pitfalls and risks. Key challenges include data quality issues, where biases in training data can lead to skewed or unfair outputs, potentially perpetuating harmful stereotypes or even violating regulations. Security vulnerabilities such as prompt injections and data leakage pose significant threats, compromising data integrity. Additionally, overreliance on LLMs can result in the spread of misinformation, as these models may generate plausible-sounding but incorrect information. Furthermore, high operational costs and the need for human oversight outputs add complexity to their implementation. Addressing these risks requires robust governance, human intervention and ongoing approach validation.

Will AI replace human ingenuity?

Human collaboration and ingenuity are indispensable in developing complex AI/ML applications. The synergy between humans and AI leverages the strengths of both, enhancing creativity, productivity, and problem-solving. Human intuition, cultural intelligence, and contextual understanding complement AI’s computational and analytical abilities, leading to novel advancements. Until true AGI exists, disruptive ideas will likely rely on human ingenuity.

In this collaborative framework, humans provide ethical judgment and oversight, while AI offers tools and insights to augment creativity. Multidisciplinary teams with diverse skills are essential for tackling complex technology projects, fostering innovative ideas, and ensuring comprehensive problem-solving. 

AI further enhances teamwork by predicting interpersonal affinity and improving communication, enabling more effective collaboration. Integrating human ingenuity with AI accelerates innovation and ensures systems are developed with an understanding of human needs and ethical considerations. This approach is vital for successful AI/ML application development.

Innovation in manufacturing and process industries requires more than technical expertise – it demands a deep understanding of market dynamics, ecosystem integration, and the responsible use of technologies like robotics and AI.

Helbling combines advanced technological capabilities with strategic insight to tackle challenges, optimize operations, and create value-add solutions. Our expertise spans business model development, process optimization, and organizational transformation, thus ensuring impactful innovation.

Through our experience, knowledge of technology, and proven approach, we help clients deliver results while shaping a responsible, future-ready industry.